Localising accurate brain regions needs careful evaluation in each experimental species due to their individual variability. However, the function and connectivity of brain areas is commonly studied using a single-subject cranial landmark-based stereotactic atlas in animal neuroscience. Here, we address this issue in a small primate, the common marmoset, which is increasingly widely used in systems neuroscience. We developed a non-invasive multi-modal neuroimaging-based targeting pipeline, which accounts for intersubject anatomical variability in cranial and cortical landmarks in marmosets. This methodology allowed creation of multi-modal templates (MarmosetRIKEN20) including head CT and brain MR images, embedded in coordinate systems of anterior and posterior commissures (AC-PC) and CIFTI grayordinates. We found that the horizontal plane of the stereotactic coordinate was significantly rotated in pitch relative to the AC-PC coordinate system , and had a significant bias and uncertainty due to positioning procedures. We also found that many common cranial and brain landmarks  vary in location across subjects and are substantial relative to average marmoset cortical area dimensions. Combining the neuroimaging-based targeting pipeline with robot-guided surgery enabled proof-of-concept targeting of deep brain structures with an accuracy of 0.2 mm. Altogether, our findings demonstrate substantial intersubject variability in marmoset brain and cranial landmarks, implying that subject-specific neuroimaging-based localization is needed for precision targeting in marmosets. The population-based templates and atlases in grayordinates, created for the first time in marmoset monkeys, should help bridging between macroscale and microscale analyses. For example, the brain volume of marmosets is likely more variable than inbred laboratory strains of rodents: the coefficient of variation (COV) of brain volume is 2.3% in mice  coordinate system is another approach originally developed for human neurosurgery and is now routinely used in human neuroimaging. The pioneering work of Tarailach et al.  used thiNeuroimaging-based systems use all structural features  for registration across subjects but in practice rarely achieve precise alignment of human cerebral cortex owing to the complexity and variability of cortical folding. This has been addressed by accurate cortical segmentation and surface reconstruction by treating the cortex as a 2D sheet-like structure . This apgrayordinate system (type 4)  ster(type 4) . We deve(type 4) , robust (type 4) , and an (type 4) . Multi-m2. . For cross-subject standardisation, we generated multi-modal cranial bone, brain and cortical templates of the marmoset (“MarmosetRIKEN20”), which were embedded in AC-PC coordinates and grayordinates using MRI (N = 20) and CT data (N = 10) using the HCP-NHP pipeline. Three animal experiments were conducted: 1) evaluation of the accuracy of the multi-modal brain targeting system and investigation of the intersubject variability of cranial landmarks (N = 10) and cortical landmarks and subcortical structures (N = 20) including cortical sulci , lateral and calcarine sulci), and subcortical structures, 2) assessment of the reproducibility of stereotactic positioning (N = 5), 3) a proof-of-concept application of the multi-modal brain targeting system to image-guided neurosurgery (N = 1). All the MRI images in this article were obtained using MRI scanner  equipped with a custom-made 16-ch marmoset head coil  plus atropine sulphate (50 μg/kg). After sedation and respiration were stabilised, the anaesthesia level was maintained with inhaled isoflurane (0.5 %), and intravenous infusion of dexmedetomidine (5.0 μg/kg/hr). Physiology was monitored using a pulse oximeter ; pulse (120 bpm/min) and oxygen saturation (94 ~ 98 %) were maintained by adjusting the flow rate of anaesthetic gas. Rectal temperature was monitored , and maintained at around 34°C using a custom-made warm water circulation system.The registration accuracy of the multi-modal brain targeting system was evaluated using CT and MRI. In each animal, the two scans were performed on the same day on a total of ten marmosets  over a period of ~2 hours, during which the custom-made plastic head holder with the multi-modal marker was attached to the head. The animals were pretreated with an intramuscular injection of ketamine (30 mg/kg) and dexmedetomidine  equipped with a custom-made 16-ch marmoset head coil . T1-weig2.2.Previous studies have not reported the reproducibility of ‘gold-standard’ stereotactic positioning in marmosets. We carried out a rigorous assessment of the bias and reproducibility of stereotaxic positioning using CT imaging . Marmoset heads were fixed to the stereotactic device , which w2.3.The multi-modal brain targeting system was applied to image-guided neurosurgery in marmosets, and its spatial accuracy to target deep brain structures was evaluated. Specifically, the aim of the surgery was to insert a guide cannula into the caudate nucleus (Cau) or substantia nigra (SN) to administer α-synuclein to induce Parkinson’s Disease-like symptoms in marmosets .Pre-surgery, MRI and CT experiments were performed to guide surgical planning: MRI was used to identify target areas (Cau and SN) and to determine the projection trajectory for surgical operation  and recoFor surgery, the animal was first anaesthetised with a combination of 0.12 mg/kg medetomidine (0.12 mg/kg), midazolam (0.6 mg/kg), and butorphanol (0.8 mg/kg) (i.m.). The anaesthesia level was maintained with a half volume of the initial anaesthesia dose every two hours. The head of the animal was fixed in the stereotactic cassette of the microsurgical neuronavigation robot . The robotic components were calibrated in a registration step beforehand . After incision of the skin over the cranium, two cranial landmarks were identified both in a real space with the robot’s laser pointer and in the CT image and used for initialising the registration between the surgical field and the CT image. Then a cranial surface was reconstructed from a point cloud dataset that was scanned using the robot’s laser pointer. Using the CT, the cranial bone was segmented and used to create the CT image-derived cranial surface. The two surfaces were co-registered to each other using the robot’s computer. The target points were defined in the individual brain’s real physical AC-PC native coordinates  and the coordinates were registered to robot’s coordinates. The trajectories of the insertion needle were planned using the robot’s controller to define appropriate entry holes and paths for SN and Cau. The cranium was drilled to make these two entry holes (w/diameter of 1 mm), placed in the medial frontal and parietal areas, to insert guide cannulas into the Cau and SN, respectively. The planned trajectories avoided passing through the lateral ventricles so as to avoid dislocating or deforming the brain . The durPost-surgery, an MRI experiment was performed to evaluate the position of the cannulae in relation to the target (Cau or SN). Because the head together with the attached cannula was larger than the inner size of the marmoset head coil, the scan was performed using a larger 24-channel head coil originally designed for macaque monkeys . Scannin2.4.https://github.com/Washington-University/NHPPipelines), which includes three structural pipelines  to generate cortical surfaces models of each marmoset hemisphere and register them to a standard grayordinates meshes in CIFTI (Connectivity Informatics Technology Initiative) format  format , a data ) format .https://github.com/RIKENBCIL/MultimodalRigidTransform). Then, for BBR, the initialised CT image was threshold at a value of −250, so that images included voxels with soft tissues and bones, then segmented using FSL FAST, and the output of the bone segmentation was fed as a boundary prior into the BBR registration to T2w (in AC-PC native coordinates). The default value of the BBR slope (−0.5) was used. For BBR between CT and T2w, we used ‘epi_reg’ in FSL by specifying CT volume as <whole head T1w image> and T2w image as <EPI image> of epi_reg inputs. We used the T2w for registering CT to MRI images, based on a preliminary analysis that showed the T2w to work better than the T1w because T2w has clear contrast both at the inner and outer boundary of cranial bone. For evaluation of registration, the minimum cost of FSL BBR was calculated using a schedule file ($FSLDIR/etc/flirtsch/measurecost1.sch). The ‘ground truth’ stereotactic coordinates were determined based on the CT image-derived cranial landmarks in each animal  and species-specific configuration that scaled size-dependent variables  were aligned to the individual’s AC-PC native coordinates  using a ariables . The linThe MarmosetRIKEN20 template was created from 20 marmoset  scans using high-resolution T1w images and non-linear registration between subjects using FNIRT. The registrations were iterated three times, with ‘de-drifting’ after each iteration, i.e., removal of the ‘drift’ in mean spatial locations that can occur with registration  in orderIntensity-Cor.sh using fsl_anat in FSL and FreeSurfer normalisation algorithms, mri_normlize. Subcortical segmentation was done using a customised probabilistic template of marmosets using FreeSurfer Gaussian Classifier Atlas   and maximum search angle  to adjust for the lissencephalic marmoset brain  were non-linearly warped in 3D to the standard AC-PC template coordinates. The subcortical segmentations of 19 parcels were resampled to a volume with a spatial resolution of 0.8 mm isotropic. The initial cortical surface registration of FreeSurfer concatenated with a group registration across left and right hemispheres (MSMSulc) based on folding maps (FreeSurfer ‘sulc’) to an average folding map created from 20 marmoset brains. The T1w divided by T2w image was used for generating cortical myelin maps, after removal of any low spatial frequency intensity biases using the smoothed (sigma=3mm) difference with a reference myelin map  and 4056 voxels in the subcortical structures   and thenet brain . As a retemplate . Then, tispheres  using a ispheres ; 2018. Telin map . All theructures . The meatures (2 2.5.d) between the centroid of each corresponding marker point  in the registered CT vs reference MR images.The CT and MR image alignment accuracy was calculated using marker registration error (MRE), which is determined as the root-mean-square of distances  of the AC-PC coordinates compared with the ‘true’ (image-based) stereotactic coordinates. The brain and intracranial volume were obtained in AC-PC native coordinates from segmented T1w and CT images, respectively. In addition, stereotactic surgery reference (bregma) and cephalometric  points were identified from the CT in the native AC-PC coordinates, based on a previously described method . The lanWe also investigated cortical surface landmark intersubject variability. Specifically, we focused on the intraparietal sulcus (IPS) because it is a recognizable landmark in marmosets  Chaplin. We quanWe also evaluated the average and variability for the volumes of subcortical regions across subjects. The high-resolution non-linear registration warp field was applied to the 11 subcortical atlas regions  and embedded in the T1w AC-PC native coordinates of each animal. The volume and the coordinate of the centroid was evaluated in each animal and the mean and standard deviation were calculated across subjects (N = 20). Six distances between the landmarks including brain length, brain width, anterior-posterior length of corpus callosum, anterior tip of frontal pole to anterior tip of temporal pole, anterior tip of temporal pole to posterior tip of lateral sulcus, anterior to posterior tip of calcarine sulcus see  were als2.7.The reproducibility of manual positioning of the cranium within the stereotactic device (device-based stereotactic coordinates) was investigated using repeated mounting  and bias was determined by comparison with the ‘true’ (image-based) stereotactic coordinates. After each mounting, the marmoset head and stereotactic device was scanned using CT. All the CT images were registered using a rigid-body transformation by weighting the mask for the stereotactic device, resulting in the same location relative to the stereotactic device, which we refer to as device-based stereotactic coordinates that include experimenter’s fixation errors. Then, the error between device-based and ‘true’ (image-based) stereotactic coordinates were estimated by using FSL Nudge and a rigid-body transformation  was estimated by the target error defined as the distance between the pre-operational plan in the SN and the postoperative trajectory of the guide cannula. The target location was determined using the preoperative MR image, and the trajectory of the guide cannula was evaluated using the postoperative MR image. The orthogonal distance between the preoperative target point and actual operative trajectory was calculated to estimate the target error.3.3.1.p-values ≤ 0.05, one-way repeated measures ANOVA) (> 1.0 mm) can be ascribed to initialization failure (> 1.0 mm) was very high for software-based methods, ranging from 0.3 to 1.0 , whereas it was zero using MBFR. The high initialization failure of software-based methods may be ascribed to the sphere-like shape of the marmoset head. The failed registration of BBR resulted in higher values of the minimum cost (> 0.8), whereas those of the successful registrations were reasonably small . When the BBR followed the MBFR, there were no failures in any subjects, and it resulted in a small number of min costs (0.68 ± 0.05). Importantly, while this MBFR+BBR approach resulted in relatively higher values of MRE than with a MBFR only approach, this is likely due to circularity in defining the MRE based on the MBFR landmarks, as the registration of the brain and cranium were improved for MBFR+BBR compared with MBFR by visual inspection of all ten subjects (The CT to MRI MRE see  was comps ANOVA) . The lar failure . Initialsubjects ,c. ThereAlthough the MBFR showed 100% success rate of the registration and alignment was fairly good, a careful inspection revealed subtle  misalignments at the cranium-brain interface in some of the subjects . To over3.2.3 and 6,912 ± 470 mm 3 for brain and cranial cavity, respectively. The intersubject variability (coefficient of variation) was 8.5% and 6.8% respectively. Cranium contours were also highly variable across subjects both in ‘true’ image-based stereotactic coordinates  in the ‘true’ (image-based) stereotactic coordinates, (b) the AC-PC native coordinates and (c) in the AC-PC template coordinates. The crosshair shows the origins (mid interauricular line in stereotactic and the centre of AC in AC-PC coordinates). Cranial position was tilted downwards (pitch) from AC-PC native coordinates to stereotactic coordinates , whereas roll, 0.6 ± 0.1° and yaw 0.2 ± 0.6°. Note that the cross-subject variability of the cranial contours in stereotactic coordinates are relatively small in the areas close to the origin but large in the distant areas from the origin, particularly in the dorsal convexity of the cranium. In contrast, the extent of the cross-subject variability is similar in the dorsal, ventral and fronto-occipital areas in AC-PC coordinates. The cross-subject variability in the AC-PC template was smaller than the AC-PC native coordinates, suggesting successful non-linear registration of the brain and cranium between subjects. Study ID: The cranial bone contours, obtained using CT (N = 10), are displayed in black lines 3.3.The errors of manual positioning of the cranium are shown in There were trends of rotation biases in pitch  and roll (rotation in Y-axis) , but not yaw (rotation in Z-axis)   e. The p3.4.Intersubject variations of the positions of the bregma in top-to-bottom view of cranium are shown in Intersubject variation of cortical landmarks  is shown in Intersubject average and variations in the volume of brain and subcortical structures are shown in 3.5.Using the multi-modal brain targeting system we generated multi-modal MRI (N = 20) and CT (N = 10) AC-PC templates . These t3.6.Distinct neurosurgical strategies guiding surgical instruments for operations into cortical or subcortical locations are illustrated in Comparison between the registration guided surgery plan and postoperative MR image demonstrates precise insertion of the guiding cannula deep into the brain . The can4.The marmoset is an increasingly important NHP laboratory model in neuroscience and biomedical research due to its evolutionary proximity to humans relative to intensively studied rodents , and com4.1.We demonstrated that image alignment using a combination of MBFR initialization and BBR fine-tuning allows more robust and accurate registration as compared to software-only or marker only methods. MBFR was effective for robust initialization, which has been often problematic in software-based registration . Indeed,4.2.Using the multi-modal brain targeting system, we demonstrated substantial intersubject variability of cranial and brain landmarks, particularly the bregma. This intersubject variability causes uncertainty in conventional stereotactic surgery. Bregma location varied by 2.0 mm (in 2SD) in the anterior-posterior direction across marmosets ,7a. PrevThe intersubject variability of cortical landmarks is also significant in marmosets. The variability of brain organisation is of particular interest in this species as social behaviours and personality are significantly variable . Since mMarmoset electrophysiological recordings  and tracTaken together, we conclude that cranial and brain surface landmarks are not precise reference points to guide stereotactic surgery in the small NHP brain. Instead, we argue that surgical planning in small NHPs may benefit from being specifically designed according to each subject’s own anatomy in a grayordinate system based on multi-modal neuroimaging data. Recent human neuroimaging studies suggest that intersubject alignment based on the highly variable folding/sulcal patterns fail to achieve accurate cortical functional localization  relative to the AC-PC plane (upward by 3 to 15 °) relative to AC-PC plane (upward direction by 10°) with respect to the AC-PC plane (downward direction) of the stereotactic coordinate relative to AC-PC plane, whereas species  with relatively smaller eyes tend to have a smaller or negative pitch . Indeed, the volume ratio of eyeball to brain is sub-stantially larger in marmoset (10%) . The marmoset stereotactic horizontal plane is tilted by + 10.0° ± 1.3 pitch   in compaet (10%)  and humaet (10%) .4.5.The combination of MBFR and BBR enabled robust and accurate cross-modal registration between MRI, CT, and the surgical device ,9. MBFR 2 (2 (minimum of 0.18 mm 2 in area 25). This finding suggests that the minimum desired accuracy to target the smallest cortical areas is 0.4 ×0.4 mm. Our proof-of-concept MBFR and BBR-guided robot microsurgery suggests that such accuracy may be achieved even for deep brain structures   is reported to be as large as 0.5 to 3mm .High registration accuracy is critical to neurosurgery of small regions/areas. Since the average marmoset cortical hemisphere surface area is 9.9 cm 2  and numb.2 mm, 2 , number .2 mm, 2  and the  5 mm 2) . Since f 5 mm 2) , surgica 5 mm 2) , whereas 5 mm 2) . In elecOverall, the image-guided robot microsurgery improved the utility, flexibility and accuracy in a variety of interventional experimental procedures. A similar MRI-guided approach was recently demonstrated in the marmoset , however5.In this study, we evaluated the accuracy of different brain coordinate systems to target specific brain structures in marmosets. We found substantial intersubject variability in brain and cranial landmarks in marmosets. In particular, the variabilities of the cranial landmarks  are substantial enough to bias the brain orientation in surgical interventions. Thus, it is recommended to use the brain image and/or cranial landmarks for spatial localization. The population-based volume and surface templates and atlas in grayordinates were created for the first time in marmoset monkeys, which may provide a basis for accurately combining function and histology data in future.1


The European impact of the clinical high risk for psychosis (CHR-P) paradigm is constrained by the lack of critical mass (detection) to power prognostic and preventive interventions.An ITAlian partnership for psychosis prevention (ITAPP) was created across CHR-P centers, which were surveyed to describe: (a) service, catchment area, and outreach; (b) service users; and (c) interventions and outcomes. Descriptive statistics and Kaplan–Meier failure function complemented the analyses.The ITAPP included five CHR-P clinical academic centers established from 2007 to 2018, serving about 13 million inhabitants, with a recruitment capacity of 277 CHR-P individuals . All centers were multidisciplinary and included adolescents and young adults  primarily recruited through healthcare services. The comprehensive assessment of at-risk mental state was the most widely used instrument, while the duration of follow-up, type of outreach, and preventive interventions were heterogeneous. Across 205 CHR-P individuals with follow up (663.7 days ± 551.7), the cumulative risk of psychosis increased from 8.7% (95% CI 5.3–14.1) at 1 year to 15.9% (95% CI 10.6–23.3) at 2 years, 21.8% (95% CI 14.9–31.3) at 3 years, 34.8% (95% CI 24.5–47.9) at 4 years, and 51.9% (95% CI 36.3–69.6) at 5 years.The ITAPP is one of the few CHR-P clinical research partnerships in Europe for fostering detection, prognosis, and preventive care, as well as for translating research innovations into practice. Indicated prevention implemented in specialized clinical high risk for psychosis (CHR-P)  servicesCHR-P individuals are challenging to detect and follow up. Detection of most individuals at-risk for psychosis is one of the main barriers toward the implementation of the CHR-P paradigm in real-word clinical scenarios .Furthermore, meta-analytic evidence shows that only about 20% of CHR-P individuals develop a psychotic disorder after 2 years from ascertainment . It is tImplementing large-scale collaborations that focuses on specialized CHR-P clinical services  is the mThe primary aim of the current study is to fill this gap by presenting an innovative ITAlian partnership for psychosis prevention (ITAPP). The core findings will be discussed to provide directions to advance and implement clinical research collaborations in the CHR-P field in Europe, and therefore advance knowledge for the potential benefit of many young people at risk of developing this disorder.This manuscript originates from a workshop on CHR-P services in Italy, held on two occasions . Leading clinical and academic centers for psychosis prevention in Italy  attended the workshop. We leveraged an empirical framework  for desp-value was set to 0.05 two-sided.When available, quantitative data were descriptively summarized using mean (and median) and SD for continuous variables and frequencies for categorical variables. Furthermore, for each CHR-P service, we collected the baseline sample size, the individual follow-up time, and the number of events (transition to psychosis from a CHR-P stage). The ascertainment of the CHR-P state and psychotic onset were determined through standardized psychometric instruments, including the comprehensive assessment of at-risk mental state (CAARMS) ; the strThe CHR-P center in Pavia encompasses two main sites: a child and adolescent neuropsychiatric unit and an outpatient clinic for young adults.The child and adolescent neuropsychiatry unit at the IRCCS Istituto Neurologico Casimiro Mondino was set up in 2007. This unit offers assessment and preventive care to help-seeking children and adolescents under the age of 18 years as part of an integrated team adopting principles of early intervention in the context of existing mental health services. The outpatient clinic is a standalone CHR-P service set up in 2019 at the Department of Brain and Behavioral Sciences. This service targets young adults (aged 18–35) with potentially emerging severe mental disorders (including bipolar and depression) and works closely with local adult psychiatric mental health services.The research activities of these two units are embedded with those of the University of Pavia. The clinical team includes psychiatrists, psychologists, nurses, trainees, and social workers. The catchment area extends from Pavia and its surroundings  to the Lombardy region , with additional CHR-P referrals routinely received from all over Italy.The primary referral sources for CHR-P are pediatricians, general practitioners, other child and adolescent mental health services in the community, and self-referrals. This center is implementing a digital outreach for CHR-P.This center treated 129 CHR-P individuals over the past years. Being mainly embedded in child and adolescent mental health services, CHR-P mean age and age range in this site are lower than those observed in the other Italian sites . The assCHR-P individuals are actively followed up over time. A yearly routine CAARMS assessment is offered to all individuals, with contingent assessments upon eventual clinical deterioration. The main outcomes of interest are psychotic onset, functioning , cognition, persistence/remission of CHR-P criteria, and mental health comorbidities.This center provides integrated interventions , which are mainly aimed at improving the mental health of young CHR-P individuals and their comorbidities.The Individuazione Precoce del Rischio Psicotico(IPRR) CHR-P center is a section of a general adult mental health service. It was set up in 2015 to offer assessment and preventive care to help-seeking young adults (aged 18 and above). The is an integrated service that adopts principles of early intervention in the context of an outpatient clinic dedicated to the treatment of psychotic disorders. The research activities of are embedded with those of the University of Bari. The clinical team includes psychiatrists, psychologists, and social workers. The catchment area includes Bari metropolitan area  and further extends to the whole region of Puglia, Italy (more than 4 million inhabitants).The main referral sources are local mental health services and general practitioners. The also provides outreach activities to improve pathways to care for CHR-P such as public engagement and screening activities in school and scheduled outreach sessions in local mental health services.The treated 72 CHR-P individuals over the past years. This unit employs the CAARMS, the SIPS, and the SPI-A. In this site, the large majority (73.6%) of CHR-P individuals met the APS criteria, and a small minority had ever used substances  when required. The main outcomes of interest are psychotic onset, functioning, cognition, persistence/remission of CHR-P criteria, and mental health comorbidities.The CHR-P center in Naples is a section of a general adult mental health service. It was set up in 2015 to offer assessment and preventive care to help-seeking young adults (aged 18 and above). This CHR-P center is an integrated service that adopts principles of early intervention in the context of an outpatient clinic dedicated to the treatment of psychotic illness. The research activities of this center are embedded with those of the University of Campania Vanvitelli. The team includes academic personnel , psychiatrists (consultants and trainees), psychologists, nurses, and social workers.The catchment area consists of an established network of 13 mental health departments located in the city of Naples and across the Campania region . The main referral sources are mental health professionals, emergency departments, liaison psychiatry, general practitioners, and self-referrals.The Vanvitelli outpatient unit for psychotic disorders screens about 500 patients every year. Approximately, 5% of these patients are CHR-P. This center treated 36 CHR-P individuals over the past years.This unit uses the CAARMS and the SPI-A. The large majority (86.1%) of CHR-P individuals met the APS criteria, and a minority had ever used substances .The Centre for Translational, Phenomenological and Developmental Psychopathology (CTPDP) is an outpatient unit, which was set up in 2018. The recruitment targets of this center are children, adolescents, and young adults (age range: 11–25 years), and it consists of a standalone second-level outpatient unit performing early differential diagnosis, monitoring and treatment supervision advice in synergy with the network of local services across Umbria Region. The research activities of the CTPDP are embedded with those of the University of Perugia. Due to the circumscribed staffing of the clinical team, which includes an academic psychiatrist (25% of time), two residents (20% of time), and two volunteer psychologists in rotational training (25% of time), integrated community treatment is performed through the referring network of local MH services following consolidated local practices and habits. The catchment area of the CTPDP is the Italian region of Umbria . The CTPDP has a pan-regional outreach receiving referrals from the two local National Health Service Trusts. The referral sources are local mental health services across the Umbria region which also scrutinize potential referrals from general practitioners and pediatricians based on clinical need of care.The CTPDP included 24 CHR-P individuals (assessed with the CAARMS). About one-third of CHR-P met criteria for brief limited intermittent psychotic symptoms (36.4%) and a substantial proportion of the sample met criteria for genetic risk and deterioration syndrome see also . A minorThe also offers to the referring MH services the opportunity for regular longitudinal follow-up on a semester/annual basis, with the outcome of interests being psychotic onset, hospitalization, and symptoms trajectories.The CTPDP does not offer direct preventive care to CHR-P, but it provides comprehensive recommendations for treatment to the referring service.The CHR-P center in Milan is a section of a general adult mental health service located within the Department of Neurosciences and Mental Health of the IRCCS Ca’ Granda Ospedale Maggiore Policlinico. It was set up in 2016 to treat help-seeking adults (aged 18 and above). It is an integrated service that adopts the principles of early intervention within a larger outpatient unit for general adult psychiatry. The clinical team includes psychiatrists, psychologists, nurses, and social workers. The catchment area includes about 250,000 individuals. The main referral sources are mental health professionals, general practitioners, and self (or family)-referrals.This center treated 16 CHR-P individuals over the past few years. Standard assessment instruments include the CAARMS, the SIPS, the SPI-A, and the SPI-CY. The large majority (75.0%) of CHR-P individuals met APS criteria, and about one-third had ever used substances , for up to 6 years , across A total of 205 CHR-P individuals in the ITAPP had follow-up data . Their mThirty-seven of the 205 CHR-P subjects transitioned to a first episode of psychosis, with a mean ± SD time to conversion of 673.8 ± 551.8 days . Those nonconverted were followed up for a mean ± SD of 661.5 ± 553.3 days . The ITAPP included five CHR-P centers across Italy, with an overall recruitment capacity of 277 CHR-P individuals. All centers had strong academic links, were multidisciplinary, and provided care to both adolescents and young adults  mainly recruited through existing healthcare services. The CAARMS was the most widely used assessment instrument, while the duration of follow-up, type of outreach, and provision of preventive interventions were highly heterogeneous. Across 205 CHR-P individuals with follow-up, the cumulative risk of psychosis was 51.9% at 5 years.The five ITAPP CHR-P centers were set up between 2007 and 2018 across Northern, Central, and Southern Italy, serving a total population of about 13 million inhabitants. All centers were linked to academic departments and conducting research (see below). All ITAPP centers were targeting a transitional age (12–39 years), with minor variations across sites. This is relevant, because a large-scale meta-analysis found that 12.3% of psychotic disorders occur before the age of 18 and 47.8% before 25, with a peak onset at 20.5 years . These fThe outreach activity across ITAPP centers was heterogeneous. Most centers relied on secondary mental healthcare and a minority on primary care. Community outreach efforts were present, but limited by challenges such as the dilution of risk-enrichment and the invalidity of CHR-P assessment in the general population ,12.CHR-P recruited in ITAPP appeared slightly younger (mean age: 18.7 years) and more frequently females (53.1%) than the average CHR-P population  . These dAll ITAPP centers employed the CAARMS, with a minority additionally using the SIPS and the SPI-A/SPI-CY. There is no evidence that using different CHR-P instruments impacts the probability of developing psychosis . In lineAll ITAPP centers but one provide preventive care: psychotherapy (including psychodynamic approaches), psychosocial support, medications, cognitive remediation, physical exercise, and their combination. Therapies were heterogenous across sites, but they all aimed at treating presenting CHR-P symptoms or their mental comorbidities. While all ITAPP services routinely incorporate comprehensive needs-based interventions, only a few implemented public health initiatives to foster mental health literacy and promote good mental  and physical health . Such heThe transition risk to psychosis in ITAPP was at the highest in the first months after the initial CHR-P assessment and it did not plateau until about 4 years, in line with recent meta-analytic analyses in this field, showing that 25% of individuals at CHR-P developed psychosis within 3 years and that transition risk continued increasing in the long term . These fWe noticed differences in the cumulative risk of psychosis across different ITAPP sites. These differences might be related to the heterogeneous recruitment and sampling procedures across sites, which resulted in heterogeneous sociodemographic characteristics  of CHR-P individuals . This heConducting long-term follow-ups emerged as core empirical barrier to implementing CHR-P services in the national healthcare system. Additional challenges encompassed difficulties in CHR-P detection , the neeDespite these crucial challenges, most ITAPP centers are actively conducting CHR-P research. This level of activity includes implementation studies , local cThe ITAPP initiative has therefore the potential to significantly advance and implement clinical research collaborations in the CHR-P field in Italy, in Europe, and worldwide.The current data indicate that the ITAPP centers have the capacity to recruit meaningful samples of CHR-P individuals on the national level, to follow them up with established instruments and to offer them potentially preventive interventions. At the same time, the current study highlights important barriers to large-scale implementation of CHR-P prevention such as the lack of a standard data acquisition dataset to record individual participant data and the need of more effective interventions. Future directions include establishing a national CHR-P program using harmonized assessment and follow-up measurements and testing the feasibility of standardized preventative interventions  across the whole ITAPP CHR-P population.The ITAPP is one of the few CHR-P clinical research partnerships in Europe for fostering detection, prognosis, and preventive care, as well as for translating research innovations into practice.


Bacillus amyloliquefaciens-9 (GB-9) improved the immunity and the nonspecific immune defense system of the body. In this study, the potential role of GB-9 in improving subclinical mastitis was assessed with Radix Tetrastigmae (RT) as a positive control in subclinical mastitis Saanen dairy goats. The current data showed that GB-9 and RT significantly reduced the SCC in dairy goats. After being fed with GB-9 or RT, the decreased concentrations of malondialdehyde, IgA, IgM, IL-2, IL-4, and IL-6 were observed. The amplicon sequencing analysis of fecal samples revealed that GB-9 significantly altered the bacterial community. Bacteroides and Phascolarctobacterium were the major genera that respond to GB-9 feeding. The correlation analysis using weighted gene co-expression network analysis showed a MePink module was most associated with the serum concentrations of immunoglobulin and interleukin. The MePink module contained 89 OTUs. The feeding of GB-9 in decreasing the SCC was associated with the altered abundance of Bacteroides, which was correlated with the concentrations of immunoglobulins and chemokines. Collectively, the current data suggested that marine-derived GB-9 could be a helpful probiotic to control subclinical mastitis.Subclinical mastitis is one of the major problems affecting dairy animals’ productivity and is classified based on milk somatic cell counts (SCC). Previous data showed that marine-derived  The significant increase in the IL-2 level in dairy cows suffering from mastitis  suggestsess IL-4 . The resess IL-4 . The lowThe occurrence of SCC is related to the composition of the gut microbial community in sheep and cows ,38, and Phascolarctobacterium was related to oxidative stress in sow [Bacteroides affect the health of animals by interacting with the fecal immune system [Bacteroides and Phascolarctobacterium were the major genera altered by GB-9 compared with RT and control. The increased abundance of Phascolarctobacterium in the BS group agreed with the finding in humans that prebiotic supplementation increased the abundance of this genus [Bacteroides is a potential marker for diagnosis of subclinical mastitis. Although the lack of data on other factors in fecal content , the current data suggested that the GB-9 in decreasing the SCC was associated with the alterative profile of gut microbiota.The role of s in sow . Bacteroe system ,44,45. Tis genus . The lowis genus ,48. The With increasing pressure to reduce antibiotic usage, antibiotics are inhibited to treat the lactating goats without clinical signs in dairy farms to reduce antibiotic residues and antibiotic resistance. In the current study, the plant-derived RT was used as a positive control for the treatment of subclinical mastitis. The minor change in the alpha diversity in the RS group suggested that GB-9 and RT had different mechanisms in decreasing the SCC. The potential mechanism of RT decreasing SCC might be initiated from the activity compositions, including flavonoids, phenolic acids, and polysaccharides, proven to be anti-inflammatory and antioxidant agents ,22,23. I4/mL) and no clinical signs of mastitis were selected. The selected lactating goats with 110 ± 8 d in milk, milk yield of 1.2 ± 0.4 kg/d, average body weight (BW) of 52 ± 3 kg, and having lambed 3 times. All goats were from the same farm and were divided into three groups as follows: goats fed with basal diet , goats were fed the basal diet supplemented with 0.3% GB-9 (w/w)  [w/w) . The nutrient composition of basal diet was showen in the 9/g. The RT powder was gifted from Wanshoukang Company in Jinhua, China.Twenty-three subclinical mastitis dairy Saanen goats with positive CMT results (SCC > 800 × 100 goats) ; and goaDuring the treatment time, dairy goats were fed approximately 105% of their anticipated consumption. Feed and orts were weighed weekly. Dry matter intake was calculated based on the feed and orts offered and consumed. Feed samples were collected weekly and were stored at 20 °C until analysis for dry matter intake.The data of milk yield and milk sample of each goat was collected for 3 consecutive days at 0 and 6 weeks. A milk sample was collected from individual goats following a ratio of 3:2 (morning and afternoon) . The conBlood samples were collected from all goats at 0 and 6 weeks. Blood was collected from the posterior jugular vein of each goat from 9:00 a.m. to 10:00 a.m. The serum was separated by centrifugation. The serum levels of MDA, GSH, T-AOC, IgA, IgG, IgM, IL-2, IL-4, and IL-6 were measured using specific commercial kits  and semiautomatic equipment  ,29.Feces were collected at the end of the experiment (6 weeks). The homogenized sample was snap-frozen in liquid nitrogen and stored at −80 °C for subsequent DNA analysis.The samples’ total genome DNA was extracted using a commercial kit . DNA concentration and purity were monitored on 1% agarose gels. The V3–V4 regions of the bacterial 16S rRNA genes were amplified, sequenced, and paired-end sequenced (2 × 300 bp) on the Illumina MiSeq platform following the standard protocols .http://huttenhower.sph.harvard.edu/galaxy/root?tool_id=testtoolshed.g2.bx.psu.edu%2Frepos%2Fgeorge-weingart%2Flefse%-2FLEfSe_for%2F1.0, accessed on 18 July 2021). CCA and RDA were performed at the genus level by using the vegan package in R. Correlation heatmaps were generated using the R program pheatmap package. WGCNA analysis was performed using the WGCNA package in R, and the network was drawn by Cytoscape (Version 3.7.1).Raw reads of different samples were demultiplexed and quality-filtered following previous methods . Bioinfop < 0.05 was considered statistically significant. Correlation networks were generated using Spearman’s rank correlation coefficients and visualized using the Cytoscape. The significant correlation between bacterial genus and the immune globulins and cytokines was considered when |R| > 0.2 and p < 0.05).The data of milk performance and composition were analyzed using the one-way ANOVA with the SPSS software . The statistical analyses of serum factors and microbiol diversity were performed by one-way ANOVA. Data are presented as means plus SEM. Bacteroides and Phascolarctobacterium were the major genera response to GB-9 feeding and were positively correlated with the concentrations of IgA, IgM, IL-2, IL-4, and IL-6. Future studies are needed to identify the mechanism of GB-9 in altering fecal microbiota composition and the immune system. However, future work on the colonization and establishment of GB-9 in the gut will help understand the crosstalk between the gut microbiota  and immune system. Collectively, the current data revealed that GB-9 could be a helpful probiotic to control subclinical mastitis.With the increasing pressure on antibiotics usage, probiotics support is an ideal strategy for controlling mastitis in dairy farms. Feeding GB-9 and RT significantly reduced the SCC in dairy goats with subclinical mastitis. The lower concentration of immune and biochemical factors in serum after feeding with GB-9 indicated that this marine-derived probiotic could be used to improve the health of the mammary gland. The alteration of immune and biochemical factors in the group fed with Gb-9 was associated with gut microbiota profiling changes.


Background: Heart rate variability (HRV) and electrocardiogram (ECG)-derived respiration (EDR) have been used to detect sleep apnea (SA) for decades. The present study proposes an SA-detection algorithm using a machine-learning framework and bag-of-features (BoF) derived from an ECG spectrogram. Methods: This study was verified using overnight ECG recordings from 83 subjects with an average apnea–hypopnea index (AHI) 29.63 (/h) derived from the Physionet Apnea-ECG and National Cheng Kung University Hospital Sleep Center database. The study used signal preprocessing to filter noise and artifacts, ECG time–frequency transformation using continuous wavelet transform (CWT), BoF feature generation, machine-learning classification using support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN) classification, and cross-validation. The time length of the spectrogram was set as 10 and 60 s to examine the required minimum spectrogram window time length to achieve satisfactory accuracy. Specific frequency bands of 0.1–50, 8–50, 0.8–10, and 0–0.8 Hz were also extracted to generate the BoF to determine the band frequency best suited for SA detection. Results: The five-fold cross-validation accuracy using the BoF derived from the ECG spectrogram with 10 and 60 s time windows were 90.5% and 91.4% for the 0.1–50 Hz and 8–50 Hz frequency bands, respectively. Conclusion: An SA-detection algorithm utilizing BoF and a machine-learning framework was successfully developed in this study with satisfactory classification accuracy and high temporal resolution. Sleep apnea (SA) is a sleep disorder with high prevalence, particularly among middle-aged and elderly subjects. SA prevalence in the overall population ranges from 9% to 38% . Frost aSA episodes are generally accompanied by abnormal breathing  and relaMany studies have shown that EDR is correlated with respiratory variation ,12,13,14Several studies have investigated the association between HRV and SA, and many SA-detection algorithms were developed using the HRV parameter ,18,19,20One of the classic analysis tools for SA disorders is electrocardiogram-derived CPC sleep spectrograms using RR interval and EDR coupling characteristics. Thomas et al.  used CPCPrevious studies showed that HRV, EDR, and CPC features can be used to develop automated SA-classification algorithms. However, the RR interval and EDR need a relatively longer time to collect the data; hence, the temporal resolution is poor for algorithms based on HRV or EDR features. Sleep CPC is a good visualization tool for RR interval and EDR coupling since it can indicate sleep quality or sleep-based breathing disorders. However, CPC’s temporal resolution for sleep is also poor, as breathing- disorder patterns present large variance, making automated classification difficult. Thus, developing an automated SA algorithm with high temporal resolution was taken as the main research aim of the present study. In this work, we used ECG spectrogram features to develop an algorithm that employs bag-of-features (BoF) techniques and machine-learning classifiers to identify various patterns in SA episodes from ECG spectrograms. Penzel et al.  initiallTwo datasets, the National Cheng Kung University Hospital Sleep Center Apnea Database (NCKUHSCAD) and Physionet Apnea-ECG Database  (PAED), The 50 recordings from NCKUHSCAD were rearranged into three groups  (APEG is the abbreviation of APnEa Group) to fulfill different purposes during algorithm performance evaluation.NCKUHSCAD-APEG-A included 11 participants who provided severe SA recordings (30 < AHI ≤ 45), with an average ± standard deviation AHI of 39.25 ± 5.78/h.NCKUHSCAD-APEG-B included 35 participants who suffered from SA (AHI ≥ 10), with an average ± standard deviation AHI of 39.83 ± 23.08/h.NCKUHSCAD-APEG-C included the whole database, with an average ± standard deviation AHI of 29.02 ± 25.49/h.PAED  was adopPAED included three participant groups: A: apnea, B: borderline, and C: healthy (the control), with 20, 5, and 10 participants, respectively. Those in Group A were known to be related to people definitely suffering from obstructive SA and had total apnea durations > 100 min for each recording. The range of ages among subjects in this group was 38–63, and the AHI of this group’s subjects ranged between 21 and 83; those in Group B were borderline and had total apnea episode durations of 10–96 min. The age range within this group was 42–53, and the AHI ranged between 0 and 25; those in Group C had no obstructive SA or very low levels of disease and total apnea durations between 0 and 3 min . RecordiPAED-APEG-A included 8 participants with severe SA recordings from group A .PAED-APEG-B included participants who suffered from SA—i.e., all of group A (21 < AHI < 83) and group B . Thus, APEG-B included 1 female and 23 males, with an average ± standard deviation AHI of 41.55 ± 23.45/h, an age of 51.42 ± 6.50 years, and a weight of 93.04 ± 16.67 kg.PAED-APEG-C included the whole database (excluding b05 and c05). Thus, APEG-C included 4 females and 29 males, with an average ± standard deviation AHI of 30.23 ± 27.35/h, an age of 46.85 ± 9.80 years, and a weight of 86.67 ± 18.23 kg. This group featured the same arrangement of participants used in ,29,30.The remaining 33 recordings from the PAED  were alsThis study proposes an SA-detection algorithm using a machine-learning framework and BoF derived from ECG spectral intensity differences between SA and normal breathing. In this study, data preprocessing consisted of zero means computation and windowing preprocessing parameters. In this method, the zero-means subtract the mean from the ECG signals to eliminate trend-variation effects, and then nocturnal ECG spectra are segmented into consecutive 60 s windows (to match the database annotation), where windows with large noise are excluded for algorithm development. The PAED ,28 and NThe time–domain ECG for each window after data preprocessing was transformed into the time–frequency domain to facilitate better SA-episode classification. Continuous wavelet transform (CWT)  was usedTo observe the differences between SA episodes and normal breathing , we used clinical data from the National Cheng Kung University Hospital sleep center for ECG spectrogram observation. To achieve high-temporal-resolution pattern visualization, the different spectrogram frequency bands were extracted to classify SA based on other authors’ observations and findings ,22,31:  or bag-of-visual-words , a visuaThe two main steps in this process were codebook generation and BoF feature-vector extraction. Codebook generation extracted representative features  to describe an image. ECG spectrograms were then regarded as images, with visual words being generated as follows. Key points (points of interest) were extracted from training images using a speeded-up robust features (SURF) detector , and 64-Support vector machine (SVM) is a supervised learning model for classification and regression. The core concept of SVM is to find the hyperplane that best separates data into two classes. In binary classification, generally, p-dimensional data can be separated by a (p-1)-dimensional hyperplane. The best hyperplane is defined as that with the largest margin between the two classes, and the closest point on the hyperplane boundary is considered the support vector .k-nearest neighbor (KNN) classifier is a simple supervised learning method and uses the nearest distance approach in deciding the group of the new data in the training set. During the training phase, the feature space is split into several regions and the training data are mapped into the similar groups of feature space. The unlabeled testing data are then classified into a certain group of feature space based on the minimum distance. Distance is an important factor for the model and can be determined, e.g., by Euclidean, Mahalanobis, and cosine-distance metrics [The  metrics ,37.Ensemble learning (EL) combines multiple learning algorithms and weight sets to construct a better classifier model. Prediction using an ensemble algorithm requires extensive computation compared to using only a single model. Therefore, ensembles can compensate for poor learning algorithms by performing extra computations. EL methods generally use fast algorithms, although slower algorithms can also benefit from ensemble techniques. Many different ensemble models have been proposed, including the Bayes optimal classifier and boosting and bootstrap aggregating (bagging) techniques . EL baggk-fold cross-validation is a well-developed validation technique [k subgroups. Subsequently, each subgroup can be selected as the testing set with the remaining (k-1) subgroups as the training set. In this way, k-fold cross-validation repeats training and testing k times, and the final accuracy is the average of the k accuracy values for each iteration. In this study, the k-fold cross-validation with k = 5 was performed at the spectrogram-level instead of the participant-level, as some studies have done [echnique . The firave done ,42,43,44ave done . The experiments were executed using MATLAB R2020a software on several computers with 24 GB installed RAM, Intel® Core™ i5-8400 CPU @2.80 GHz, and NVIDIA GeForce GTX 1060 6 GB mounted graphic card. The Classification Learner toolbox from MATLAB was utilized to perform the machine-learning classification. Hyperparameter optimization was performed using nested five-fold cross-validation and grid search using a 60 s time window based on the best frequency range, 8~50 Hz, and machine-learning model construction, SVM see . Table 4SA detection in a short time window was an important consideration for this study. Therefore, we also investigated a shorter window length (10 s). For example, eleven subjects from NCKUHSCAD-APEG-A were selected, and different frequency bands were compared via five-fold cross-validation. The time window length was too short to provide variation in the lower frequency band; hence, that band was not considered in this comparison. To the best of our knowledge, our study is the first to use an ECG spectrogram for SA detection. This proposed algorithm used high-temporal resolution feature visualization of the ECG spectrogram in differentiating normal and SA breathing. Using this high-temporal resolution pattern visualization, the proposed algorithm was able to achieve high accuracy, sensitivity, and specificity in SA detection.Sleep is a dynamic situation of consciousness characterized by rapid changes in autonomic activity that regulates coronary artery tone, systemic blood pressure, and heart rate. In the analysis of 24-hour heart rate variability (HRV), a nocturnal increase in the standard deviation of mean RR intervals commonly occurrs. In the study by Zemaityte et al.  and RaetIn this study, by investigating the REM and non-REM partitions on the SA classification using PAED 60 s time window based on the best frequency range (8~50 Hz) and machine-learning model (SVM), it was concluded that the ECG variation (HRV) did not significantly affect the SA classification performance. Both REM and non-REM partitions of imbalanced and balanced datasets generated for PAED-APEG-A, PAED-APEG-B, and PAED-APEG-C groups presented a good classification performance with the average accuracy was up to 81.42% for REM stage and 79.2% for non-REM stage see . The balA more realistic scenario to the medical application, which is required to classify a new unseen subject into the model, is the so-called per-subject classification. Leave-one-subject-out cross-validation (LOSOCV) was used in this study to perform the per-subject classification. In LOSOCV, one subject is set aside for the evaluation (testing) and the model is trained on remaining subjects. The process is repeated each time with a different subject for evaluation and results are averaged over all folds (subjects).Results from k-fold cross-validation PAED 60 s time window based on 8~50 Hz frequency range and SVM classifier experimental setting demonstrates that the model almost certainly can detect subjects with disease if training and testing sets are not separated in terms of subjects, leaving data related to a subject in both sets. As the result shows, it can achieve a high level of accuracy (89.13%). With all other experimental settings remaining the same, except PAED-APEG-C group as some subjects in the Group C were excluded since they did not experience anapnea event, when the LOSOCV was applied the accuracy decreased significantly to 70% . This prQuinceno-Manrique et al. (89.02% accuracy) , Nguyen Similar to the proposed method, Singh et al.  also empAlthough the proposed algorithm exhibited excellent performance, there were several limitations in this study. First, a limited sample size from PAED was used to validate the proposed algorithm. Second, in PAED, insufficient physiological data and subject disease history was available for further analysis since such information was not provided. Mass data collection from the Sleep Center NCKUH could be a solution for these drawbacks. Third, the proposed algorithm could not be applied to patients with cardiovascular disease complications since their ECG spectrograms tended to be somewhat irregular and not affected only by SA.Future works could identify physiological meanings for the OSA features automatically extracted from the AI algorithm, test a large-scale group of participants from the sleep center database, and develop an algorithm to discriminate SA and cardiovascular disease using ECG data.This paper proposed a new algorithm to classify SA patterns from ECG spectrograms. Four different frequency bands were considered along with three classifiers. High accuracy was obtained when applying time–frequency spectrograms to SA, and the features extracted by visual classification revealed previously unknown physiological significance, such that SA detection was feasible.The algorithm provided superior accuracy compared to current common-practice approaches over generally shorter time windows (60 s) compared to those used in earlier models. Acceptable accuracy was also derived for very short time windows (10 s), highlighting the considerable flexibility in potential applications for this algorithm.


Among 10 urinary miRNAs, the levels of bta-mir-99a-5p , bta-miR-125b , bta-mir-145 , bta-mir-210 , mir-21 , and bta-mir-191  were found to be altered during different phases of buffalo estrous cycle. In contrast, bta-mir-126-3p, bta-let-7f, bta-mir-16b, and bta-mir-378 were undetected in buffalo urine. Furthermore, a validation study in an independent group of 25 buffalo heifers showed the increased levels of urinary bta-mir-99a-5p during the DE  phase as compared to the E phase. Receiver operating characteristic curve analyses also revealed the ability of urinary miR-99a-5p in distinguishing the E from the DE phase . In silico analysis further showed an enrichment of miR-99a-5p putative targets in various ovarian signaling pathways, including androgen/estrogen/progesterone biosynthesis and apoptosis signaling, implicating the role of miR-99a-5p in ovarian physiology. In conclusion, significantly lower levels of bta-mir-99a-5p at the E phase than the DE phase in buffalo urine indicate its biomarker potential, which needs to be further explored in a large cohort in the future studies.Accurate estrus detection method is the need of the hour to improve reproductive efficiency of buffaloes in dairy industry, as the currently available estrus detection methods/tools lack high sensitivity and specificity. Recently, circulating miRNAs have been shown as non-invasive biomarkers by various studies. Hence, in order to evaluate their potential as estrus biomarkers, the objective of this study was to identify and compare the levels of 10 hormone-responsive miRNAs in the urine collected at proestrus (PE), estrus (E), and diestrus (DE) phases of buffaloes ( In addition, 25 animals, which were presented for AI at the AI center, ICAR-NDRI, were considered for the validation study. The study was approved by the NDRI Institutional Animal Ethics Committee .n = 3 for discovery group and n = 25 for validation group) in 50 mL centrifuge tubes, transported to the laboratory on ice, and centrifuged at 3,000 g for 5 min at 4°C. The supernatant or cell-free urine (CFU) was transferred to another microcentrifuge tube and then either used immediately or stored in −20°C until further use. In case of the discovery group, urine was collected from different phases of three consecutive estrous cycles of each animal, but the samples that belonged to the middle estrous cycle were selected for further analysis. In validation group, urine was collected from buffaloes on day 0 before insemination and again on day 10. Estrus and DE paired samples from animals that showed typical salivary fern pattern of estrus on day 0 and were found to be non-pregnant during 60 days after AI were included in this study.Urine and saliva samples were collected in the morning time and in the evening on the day of E (day 0), proestrus (PE) (day −2), and diestrus (DE) (day 10). In case animals did not urinate for 20 min, the animals were stimulated for urination by pouring water on the rump region or by tying the animal or by offering the water to the animal. In brief, midstream urine was collected from healthy buffalo heifers (Table 2. Serum (n = 3) was used to estimate the estradiol levels using enzyme-linked immunosorbent assay–based Estradiol Estimation Assay kit (ADI-900-174 by ENZO) as per the manufacturer's protocol.Buffaloes were observed for estrus symptoms twice a day in the morning and the evening for the period of 6 months. E phase was determined by observing various signs such as visual observation , gynecoclinical examination , and biochemical confirmation  and rated as either mild, moderate, or intense as mentioned in g for 5 min at 4°C. A 10 μL of cell-free saliva was used for smear preparation on a clean glass slide for observing the salivary fern patterns under an inverted microscope  to determine the phase of an estrous cycle as per our previous study  as per the manufacturer's protocol. In brief, 250 μL of CFU was mixed with 750 μL of TRIzol LS and vortexed briefly, and the mixture was kept at room temperature for 5 min. Then, 200 μL of chloroform  was added to the mixture, vortexed for 15 s, and incubated for 15 min at room temperature followed by a centrifugation at 12,000 relative centrifugal force (rcf) for 15 min. Aqueous supernatant was transferred to a fresh Eppendorf tube, 500 μL of isopropanol was added to it, and the mixture was incubated at −20°C for 30 min. Later, it was centrifuged at 12,000 rcf for 10 min. The supernatant was discarded, and the pellet was washed with 70% ethanol. Finally, the RNA pellet was dissolved in 20 μL of nuclease-free water and then either used immediately or stored at −20°C until further use. RNA purity and concentrations were determined by using a Nanodrop spectrophotometer.Total RNA was used to prepare cDNA as per the miScript II RT kit  according to the manufacturer's protocol. In brief, 10 μL of cDNA reaction mixture containing 500 ng of the total RNA, 2 μL of 5X miScript Hispec buffer, 1 μL of RT mix, 1 μL of 10 × miScript nucleics mix provided by Qiagen miscript II kit , and 1 μL of an exogenous spiked-in miRNA control, syn-cel-miR-39-3p  was incubated at 37°C for 60 min and 95°C for 5 min. The prepared cDNA was kept at −20°C until further use.ΔCt−Δ method  or Applied Biosystems Fast 7500 Real-Time PCR system . The primers used for miRNA amplification were designed on the basis of mature miRNA sequences of bovine using miRBase 21 and procured from a commercial firm  35). In. In35). t method  by usingt method .MiRWalk, an online tool, was used to predict putative mRNA targets that might be regulated by miR-99a-5p under a threshold of 3 . The respost-hoc Tukey test or paired t-test using GraphPad Prism software 5.1. . Results are shown as the mean ± SEM. Receiver operating characteristic (ROC) curve analysis was performed using ΔCt values of the miR-99a-5p in the E and DE phase samples.Statistical analyses were performed either by one-way analysis of variance (ANOVA) followed by P < 0.05) as compared to the DE phase (16.28 ± 1.174 pg/mL).Estrus was determined by various physical indicators such as tonicity of uterus, swelling of vulva, vaginal discharge, and typical salivary fern patterns. Physical indicators were categorized as mild, moderate, and intense as shown in P < 0.05) compared to the PE phase as shown in We selected 10 hormone-responsive miRNA candidates identified on the basis of literature  for qRT-P < 0.0001) in the DE phase as compared to the E phase as shown in P = 0.076) as shown in mir-99a-5p levels were analyzed in another group of 25 buffaloes on the day of the E and DE phases during an estrous cycle. mir-99a-5p levels were observed to be significantly increased  a first insight of hormone-responsive miRNAs levels in buffalo urine using real-time PCR, (ii) a potential of urinary cell-free miR-99a-5p as estrus biomarker in bovine, and (iii) a clue that ovarian-derived miRNAs may get filtered out in buffalo urine. Most importantly, ROC curve analysis showed that urinary levels of miR-99a-5p in buffalo can moderately distinguish the E from DE phases of an estrous cycle, further suggesting its biomarker potential in estrus detection that needs to be further explored in future either alone or in combination with other miRNAs to improve its sensitivity and specificity.The present study reported significantly lower levels of urinary cell-free mir-99a-5p at the E phase as compared to the DE phase in buffalo. This may be helpful for the development of mir-99a-5p–based estrus detection kit in the near future.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/The animal study was reviewed and approved by IAEC, NDRI, Karnal.AH and PR: performed the research, methodology, and data analysis. RC: writing—original draft. SO: conceptualization and supervision. DS: conceptualization, supervision, and experimental design. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


There was a median (IQR) of 30.5% (26.2–34.4) reduction in body weight. Plasma glucose, glycosylated hemoglobin, fasting insulin and HOMA-index decreased at 3, 6 and 12 months of follow-up . The plasma aldosterone concentration (median (IQR)) also decreased at 12 months  to 65.4 , p = 0.003). Both leptin and hs-CRP decreased (p < 0.001) and adiponectine levels increased at 12 months post-BS (p = 0.017). Linear mixed-models showed that body weight  and plasma aldosterone  were the independent variables for changes in eGFR. Conversely, glycosylated hemoglobin was the only independent variable for changes in albuminuria . In conclusion, body weight and aldosterone are the main factors that mediate eGFR changes in obesity and BS, while albuminuria is associated with glucose homeostasis.Obesity-related hyperfiltration leads to an increased glomerular filtration rate (GFR) and hyperalbuminuria. These changes are reversible after bariatric surgery (BS). We aimed to explore obesity-related renal changes post-BS and to seek potential mechanisms. Sixty-two individuals with severe obesity were prospectively examined before and 3, 6 and 12 months post-BS. Anthropometric and laboratory data, 24 h-blood pressure, renin-angiotensin-aldosterone system (RAS) components, adipokines and inflammatory markers were determined. Both estimated GFR (eGFR) and albuminuria decreased from the baseline at all follow-up times ( Worldwide obesity has nearly tripled since 1975 . In addiHere we sought to assess changes in renal function at different follow-up times in patients with severe obesity undergoing BS. In addition, we explored the possible role of the renin-angiotensin aldosterone system (RAS), changes in glucose metabolism, and inflammation as potential mechanisms mediating these changes.2 or grade II obesity (BMI > 35 kg/m2) plus associated comorbidities . Patients with any endocrine disease causing obesity or severe psychiatric diseases were excluded. Detailed information on the trial was provided by qualified professionals of the Hypertension and Vascular Risk Unit . The exclusion criteria comprised the ruling out of the BS program for any reason or the refusal to give consent. The trial was approved by the local institutional Ethic Committee in accordance with the Declaration of Helsinki, and written informed consent was obtained from all participants.The BARIHTA study is a prospective observational trial in a cohort of consecutively enrolled patients with severe obesity scheduled to undergo BS . Details about BARIHTA trials have been previously published . Thus, tHere we evaluate and report the effects of BS on renal function and explore its possible mechanisms by analyzing its relationship with various components of the renin-angiotensin-aldosterone system (RAS), along with inflammatory markers and adipokines, as previously specified per protocol.Demographic, anthropometric and clinical data were recorded from all participants as a baseline. Anthropometric characteristics, pharmacological treatment, office- and 24 h-ambulatory-blood pressure (BP) recordings, routine laboratory tests, including renal function as assessed by the estimated glomerular filtration rate (eGFR) and by determining albuminuria, and determinations of components of the RAS, adipokines and inflammatory markers, were obtained at baseline and 1, 3, 6 and 12 months after surgery. Changes at follow-ups are evaluated from three months on to avoid the major hemodynamic instability one month after BS. Hypertension was considered if previously diagnosed and/or if the baseline 24 h-BP was ≥130/80 mmHg. Diabetes mellitus (DM) was considered if the patient received antidiabetic treatment or had ≥2 fasting plasma glucose determinations ≥126 mg/dL or if glycosylated haemoglobin A1c was >6.5%.About one-third of the study population was under treatment with at least one drug that interfered with the RAS. Given that these drugs could introduce a bias by interfering with renal function parameters, the main analyzes were performed separately in both the entire cohort and in the untreated patients.® NG-ambulatory blood pressure (NG-ABPM) device by IEM, Stolberg, Germany. The monitor was placed on a working day between 08:00–10:00 h A.M., and after a 5 min rest, BP was consecutively determined four times at 1-min intervals. The mean was established as office BP. Brachial artery waveforms were then automatically recorded at 20-min intervals. Suitably sized cuffs were used according to the arm circumference measured in each study visit. All patients had recordings of good technical quality . If not, a new ambulatory-BP-monitoring (ABPM) was repeated within 1 week.Brachial-BP measurements and calculation of central-BP and other arterial parameters through the oscillometric method  were obtained from a Mobil-O-GraphUrinary Albumin ExcretionUrinary albumin excretion  was determined before BS and at the determined follow-up time-points and measured as the average of urinary albumin/creatinine ratio (ACR) from 2 fresh first-morning-void urine samples obtained on separate days. Microalbuminuria was defined as an ACR ≥ 30 mg/g. Serum Creatinine and eGFRSerum creatinine (SCr) was measured by an enzymatic modified Jaffe reaction  using the Hitachi Modular System Analyzer (Roche Diagnostics), consistent with the current National Kidney Disease Education Program recommendations for standardizing SCr measurement . The intThere is no current agreement as to the best method to estimate the GFR in individuals with severe obesity. However, in a recently reported study , the modRenin-Angiotensin-Aldosterone System (RAAS) ComponentsPlasma renin activity (PRA) and plasma aldosterone concentration, as well as angiotensin-converting enzyme (ACE) and angiotensin-converting enzyme-2 (ACE2) activities, were measured by validated laboratory methods . DetailsAdipokines and Inflammatory ParametersLeptin, adiponectin, and other cytokines and inflammatory markers, e.g., resistin, angiopoietin-2, MCP-1 and high-sensitivity C-reactive protein (hs-CRP), were also determined. See 2, as a first-step treatment in cases with a body mass index (BMI) > 50 kg/m2 and when drug malabsorption was to be avoided [Either laparoscopic Roux-en-Y gastric bypass (LRYGB) or laparoscopic sleeve gastrectomy (LSG) were performed, and any of these two were chosen for each patient based on clinical criteria and the consensus of the Bariatric Surgery Unit. In this line, LSG was preferred in younger patients, in those with a BMI ranging from 35–40 kg/m avoided . The LRYp-value. A change was considered significant if the two-side alpha level was ≤0.05. We used the statistical package SPSS for Windows version 25.0 , and STATA package version 15 , for statistical analysis.Elementary statistical methods were applied with statistical package SPSS for Windows version 25.0 . The normality assumption for continuous variables was tested through the Kolmogorov–Smirnov test. Variables fulfilling this normality assumption were summarized as the mean ± S.D. or the median  otherwise. Categorical data were presented as frequencies and percentages. Comparisons of analyzed variables between two observed periods were carried out by paired t tests or Wilcoxon signed rank tests. Pearson or Spearman correlation coefficients were used for testing bivariate correlations as appropriate. Separate linear mixed-models were built for both the variation of eGFR-CG and the variation of albuminuria. All variables which deviate from the normal distribution were log-transformed (ln) before being introduced into the model. In these models, data were expressed as regression coefficient, 95% confidence interval (95% CI) and About one-third of the study population received treatment with one or more drugs that interfered with RAS. Given that these drugs could introduce a bias by interfering with renal function parameters, the main analyses were performed separately in both the entire cohort and in the untreated patients.2, before BS. None of the patients had chronic kidney disease based on the estimated glomerular filtration rate, nor did any of them die at follow-up.Sixty-two patients completed the BARIHTA study, and information on renal changes was available for all of them at the baseline and follow-ups. A flowchart is supplied . Baselin2 (p < 0.001), reflecting the hyperfiltration that characterizes patients with severe obesity. In addition, the albuminuria, as measured by the log-transformed albumin-creatinine ratio (lnACR), decreased from 1.85 ± 1.08 to 1.56 ± 0.73 (p = 0.056). Both the estimated GFR (p for trend <0.001 for both). The estimated GFR decreased from 155.9 ± 36.3 to 127.7 ± 27.4 mL/min/1.73 mated GFR A and theated GFR B experie2 at baseline and 29.7 ± 4.8 kg/m2 one year after BS (p < 0.001). p < 0.001). A waist circumference (cm) decrease was confirmed in both men (140.2 ± 14.3 vs. 111.4 ± 16.3) and women (129.8 ± 10.1 vs. 103.4 ± 11.7), (p < 0.001 for both comparisons). Overall, there was a median (IQR) 30.5% (26.2–34.4) reduction in body weight 12 months after BS. Body mass index was 42.7 ± 5.6 kg/mp = 0.01 after adjustment for age and sex.As previously reported , office p = 0.001) and waist circumference .There was a statistically significant correlation between the variation at 12 months of peripheral 24-h systolic blood pressure (SBP) and the variation of both body weight .p for trend < 0.001 for all).The changes at 12 months after BS in various components of the RAS were also assessed. As expected, there was a statistically significant decrease in plasma renin activity and aldosterone plasma concentration, as well as an increase in the ACEactivity/ACE2 activity ratio after BS see . These cThere were statistically significant changes 12 months after BS in the explored adipokines and inflammatory markers . As seenSeparate mixed-models were built for both the variation of eGFR-CG and the variation of albuminuria . The tesThe models with a better performance show that the statistically significant independent variables for eGFR A were boThe main finding of this study is that in obese patients undergoing BS the mechanisms by which the estimated glomerular filtration rate and albuminuria return to normal values are possibly different. Thus, we demonstrate that normalization of eGFR is associated with a decrease in both body weight and plasma aldosterone concentration, while a decrease in albuminuria is directly correlated with an improvement in glucose metabolism.Weight excess is associated with an altered renal haemodynamic profile, i.e., an increased GFR relative to effective renal plasma flow, resulting in an increased filtration fraction . HyperfiSeveral studies have investigated the mechanisms likely to be responsible for renal changes observed in obese patients. A large number of these studies refer to hyperfiltration in general terms, focusing mainly on eGFR, especially with regard to the consequences of BS on renal function. Some of them found a relationship between the decrease in eGFR after BS and an improvement in the toxic adipokine profile observed in these patients ,9. In ouThe second relevant finding of this study is the close relationship between decreased albuminuria and improvement in all parameters of glucose metabolism. Indeed, most of the reported investigations regarding decreases in albuminuria after BS are based on cohorts of diabetic patients ,26,27,28We need to point out some limitations of the study. First, the GFR was estimated rather than measured directly. However, it should be noted that we determined the eGFR at various points over the 12 months and observed a significant decrease at any given time. In addition, although it has been suggested that weight loss-related changes in muscle mass influence eGFR to some extent, it is unlikely that a gradual decrease in eGFR over 12 months of follow-up will be accompanied by a continued decrease in muscle mass during this time. Second, for technical reasons, we were unable to determine interleukin-6 in most samples, so these data were excluded from the final analyses. Although it is a well-known marker of inflammation, we have complete data on hs-CRP, another hallmark of inflammation, and it was finally rejected that it played an important role in renal changes after adjustment for other variables. Finally, we cannot ignore the fact that the possible role of the RAS in changes in eGFR and glucose metabolism in changes in albuminuria are only hypotheses that should be confirmed in a randomized clinical trial.In conclusion, our study demonstrates that weight loss and especially decreased aldosterone levels are the main factors associated to the restoration of the abnormally increased eGFR seen in obese patients after BS. This highlights the importance of the possible role of the RAS in renal hemodynamic alterations in obese patients that ultimately impair renal function. On the other hand, we show that increased albuminuria in obese patients is related to impaired glucose metabolism, regardless of blood pressure and weight loss.


To quantify the longitudinal changes of the optic nerve head (ONH) parameters and peripapillary retinal nerve fiber layer (pRNFL) thickness in patients recovered from coronavirus disease 2019 (COVID-19) using spectral-domain optical coherence tomography (OCT) analysis.  In an observational longitudinal study, in patients recovered from COVID-19, ONH OCT images were recorded at least two weeks after recovery from the systemic disease as the baseline and after one and three-month follow-up. Ganglion cell complex (GCC) analysis, ONH parameters, and pRNFL thickness changes were measured. μm in the first post-COVID-19 month to 74 ± 10 μm in the third month (P=0.8). The average, superior, and inferior pRNFL thickness remained unchanged. The average cup volume significantly decreased from 0.27 ± 0.15 mm3 at baseline to 0.19 ± 0.15 mm3 in the third post-COVID-19 visit (P=0.028). In terms of ONH morphologies including rim, disc and cup to disc area, and the vertical and horizontal ratio, the changes were not significant over the 3-month study period. Focal loss volume and global loss volume values were not changed significantly.  A total of 36 eyes from 18 recovered COVID-19 patients including eleven (61.2%) females were studied. The average age was 35.5 ± 7.5 years. The pRNFL thickness in the nasal lower sector significantly decreased from 77 ± 18  Localized defect in the nasal lower sector of pRNFL is observed in 3-month post-recovery from COVID-19. Larger studies with longer follow-ups are required to reveal the exact changes in ONH parameters. In the early days of the coronavirus disease 2019 (COVID-19) pandemic, ocular or neurologic evaluation seemed unnecessary. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a member of the Coronaviridae family, was thought to lead to a respiratory illness, an infection in the lower respiratory tract that is transmitted especially through physical contact and respiratory droplets [SARS-CoV-2 enters different cell types and triggers the innate immune response via its main receptor, angiotensin-converting enzyme (ACE) 2 . The ACEThis longitudinal study aimed to evaluate ONH and pRNFL thickness in patients with a history of SARS-CoV-2 infection by SD-OCT and compare baseline measurements with one- and three-month follow-ups.This longitudinal study was carried out at the Khatam Eye Hospital, the referral eye center of Mashhad University of Medical Sciences (MUMS), Mashhad, Iran. The inclusion criteria were a definite history of COVID-19 confirmed by the positive test result of a nasopharyngeal swab sample with real-time reverse transcription-polymerase chain reaction (RT-PCR) and a history of recovery from the systemic symptoms for at least one week. Detailed ocular and systemic histories of all the participants were collected. All the patients included in this study were the personnel of the Khatam Eye Hospital who had recovered from COVID-19. They volunteered to go through ophthalmological examination and ONH analysis in all three follow-up visits for the objectives of the present study.The exclusion criteria were any history of refractive or intraocular surgery, history of diabetes mellitus, glaucoma, migraine, breastfeeding, current pregnancy, clinically apparent retinal disease, or autoimmune diseases. Those who had a history of hospitalization or systemic corticosteroid treatment for COVID-19 were not included. Furthermore, patients with a spherical refractive error greater than five diopters and a cylindrical refractive error of more than two diopters were also excluded. Any evidence of ocular media opacity preventing high-quality imaging or reduced OCT quality was also not included in the analysis. In addition, those with the best-corrected visual acuity less than 20/20 were also excluded from the protocol.Personnel who were infected with COVID-19 and returned to their workplace two weeks after the completion of the symptomatic period were included in the study during the first week after their return. Patients were also imaged using the same machine one and three months after their return. All imaging was performed between 11 AM and 2 PM to avoid diurnal changes in vessel density and by one operator. Patients who did not complete the follow-up imaging were excluded from the study.All the SD-OCT scans were performed with the Optovue SD-OCT machine . All measurements were performed using the automated default segmentation. We used the 3D disc image acquisition, ganglion cell complex (GCC) analysis, and ONH protocol of optic disc peripapillary evaluation to measure pRNFL thickness. GCC parameters were evaluated in this study, and they included the following: average thickness, thickness of the superior and inferior quadrant, the difference between the superior and inferior quadrant thickness (named intraeye), focal loss volume (FLV), and global loss volume (GLV).All images were centered on the optic disc and displayed a signal strength of at least 50. All images in the study were carefully reviewed by the two retina specialists (MoA and SMH) to ensure their adequate quality, resolution, optic disc acquisition, and cup and rim detection. Moreover, the images with significant motion artifacts that interfered with evaluation were not included. ONH protocol evaluates pRNFL thicknesses in eight peripapillary segments and ONH cup, disc, and rim area analysis. Moreover, macula was also analyzed using GCC analysis to evaluate ganglion cell layer thickness and focal loss volume (FLV) and global loss volume (GLV) value changes. All subjects were examined using the same machine located in Khatam Eye Hospital, Mashhad, Iran. For each subject, both eyes were included.P value of 0.05 was considered statistically significant. All statistical analyses were performed using the SPSS software for Windows (version 25).To present the data, descriptive statistics were used, including mean, median, standard deviation (SD), and range. The normal distribution of variables was tested using the Shapiro-Wilk test; and normality plots and homogeneity of variances were examined by Levene's test. To compare changes within the study subjects, generalized estimating equation analyses were performed. It should be mentioned that a The study was performed based on the tenets of the Declaration of Helsinki. Accordingly, written informed consent was obtained from all participants before enrollment, and the study was ethically approved by the Regional Committee on Medical Ethics at Mashhad University of Medical Sciences (IR.MUMS.MEDICAL.REC.1399.402).A total of 36 eyes from 18 recovered COVID-19 patients were included. The average age ± SD of participants was 35.5 ± 7.5 (25–51) years. Eleven (61.2%) of the study participants were female. None of the cases was vaccinated as no vaccine was available in the period of the study in Iran.μm in the first post-COVID-19 month to 74 ± 10 μm in the third month (P=0.038). The thickness values remained unchanged in all other sectors     .μm in three respective post-COVID-19 visits (P=0.64). An increasing pattern was observed in FLV and GLV values. The average FLV was 0.8 ± 1.2 at baseline that increased to 0.86 ± 1.32 after 1 month and continued to rise to 1.02 ± 1.53 at month 3 (P=0.07). However, the increase did not reach a statistical significance level. A similar pattern was observed in GLV in a way that the average value at baseline (2.56 ± 2.9) reached 2.9 ± 3.37 and 3.06 ± 3.2 in the first and third post-recovery month (P=0.8) ( (P=0.8) .The present study investigates the GCC analysis, pRNFL thickness, and ONH parameters in patients who recovered from COVID-19 over a 3-month follow-up period. Our results demonstrate that a localized decrease is observed in the nasal lower sector of pRNFL thickness 3 months after recovery from COVID-19. Furthermore, cup volume was significantly decreased over the study period while other pRNFL thickness and ONH parameters remained unchanged.Two possible directions exist to explain the decrease in the nasal lower sector; first, the pRNFL thicknesses are increased upon the disease onset and the resolution of changes occurs during the recovery phases. Second, there is no change in ONH parameters and only focal changes are observed upon the disease onset and afterward. Since our COVID-19 cohort was evaluated after recovery and also there was no control group, it is difficult to understand which direction is more accurate. However, based on the few reports existing in the literature, pRNFL thickness is slightly increased in the acute phase of COVID-19 , 14. FocCOVID-19 can affect the ONH through several possible mechanisms. The direct invasion of the SARS-CoV-2 virus is the first plausible mechanism. To date, the neuroinvasive behavior of the virus has been well demonstrated in both the central and peripheral nervous system , 18. TheThe effect of drugs commonly used in the treatment of COVID-19 can be another cause of pRNFL involvement. However, we could not find the reports of hydroxychloroquine , lopinavAnother mechanism could be attributed to the role of inflammation and ischemia provoked by the disease. COVID-19 can damage the endothelial cells through the release of inflammatory markers and activated complement cascades , 24. TheThe last plausible mechanism is the involvement of CNS in COVID-19. Neurological signs have been reported in 30 to 40 percent of COVID-19 patients . InteresVarious studies investigated macular or peripapillary OCT-A parameters in the follow-up of patients recovered from COVID-19 –34. HoweSeveral limitations of the present study are worth to be mentioned. First, the absence of control groups in study period unables us to compare the measured values with the eyes of the normal population. In our previous study, we used a cross-sectional case-control study protocol without follow-up of patients. Moreover, many other cross-sectional recent reports indicated defect in ONH and pRNFL, although the patients were not also followed up in these studies. In this study, we planned to evaluate the longitudinal changes, and it seems that using a control group may be redundant. However, it may be considered as a limitation to our study. Second, our small cohort of COVID-19 patients represents the mild spectrum of the disease. Therefore, the generalizability to all patients recovering from COVID-19 is reduced. Beside mild to moderate severity of the disease in our patients, our cohort of patients were relatively young and also otherwise healthy without any other systemic or ocular comorbidities. We believe that it can be considered as an advantage of our study, as if we find any change in this group of patient it may be attributable to COVID-19, by reducing power of other confounding factors. Changes may be worsened in older people or patients with systemic comorbidity. Third, both eyes of each patient were included, which may interfere with the analysis. Fourth, anosmia which can be considered a neurotropic characteristic of SARS-CoV-2 is not evaluated in the present study. Fifth, patients cannot be assured that they do not have asymptomatic COVID-19 due to the lack of a PCR test and laboratory characteristics performed at the follow-up visits. As it is not a routine procedure to apply RT-PCR test in follow-ups, we did not perform it, and it could be considered as a limitation.In conclusion, the localized defect in the nasal lower sector of pRNFL is observed in 3 months postrecovery from COVID-19. The resolution of higher pRNFL thickness proposed by other investigations may be fast. The resolution could be followed by a localized defect that implies partial recovery from the acute insult. Larger studies with longer follow-ups are required to reveal the exact changes in ONH parameters.